LEVELS OF PROCESSING IN
FACIAL MEMORY
Sarah Babcock, Rose Ann Calvieri, Lauren Cudney,
Vedran Dzebic ,Silvia Eleftheriou, and Jeff Mazurkewich,
TOPIC DEVELOPMENT

Progression of ideas for possible studies:

Initial thought: Combine spatial memory with decision
making task

Replaced spatial memory with word memory

Word memory is well studied, we wanted to approach
memory from a different angle

Memory involving different levels of processing
regarding objects

Decided to examine faces instead of objects
RATIONALE FOR THE STUDY


We encounter faces constantly, making facial
memory a crucial skill for social interactions
Examining techniques of facial memory can
potentially improve ease of everyday social
interactions
LITERATURE: CRAIK & TULVING
(1975)

Experiment


Processing words at different levels
 Subjects presented with words & asked questions to
various levels
 Shallow = same font
 Medium = counting letters in word
 Deep = synonyms
Results

Better memory recall for words processed at a deeper
level
LITERATURE: BRUCE & VALENTINE (1985)

Experiment
Priming task: Subjects were shown the name or
photo of a celebrity
 Recognition task: Subjects were then shown a series
of photos of celebrities and asked to name them
 The subject had seen either the name, same photo or
a different photo of the same celebrity in the priming
task


Results

Better memory for faces which subject’s had seen
pictures of in the priming task (same or different)
LITERATURE: GEGHMAN & MULTHAUP
(2004)

Experiment
Source memory for faces (internal or external)
 Questions were asked about faces in a presentation of
facial images
 The subject either generated the answer or the
answer was provided for them (accompanied the face)


Results

Subjects were better at source memory for faces
which asked them to generate answers (internal),
than for faces accompanied by the answers (external)
PURPOSE OF THE EXPERIMENT

Purpose:

To determine whether different questions can elicit
deeper levels of processing

To establish if deeper levels increase subsequent
memory on a facial recognition task
LEVELS OF PROCESSING

Questions:

1)
 2)
 3)
 4)
What is this person’s most attractive feature?
What job do you think this person has?
How old is this person?
What is this person’s gender?

Examine whether any of these questions will
result in deeper level of processing, measured
by accuracy of facial recognition
HYPOTHESIS

If different levels of facial processing can be
achieved, deeper level processing will lead to
better recognition of faces
Hypothesized to elicit shallower processing:
 Questions about gender and age
 Hypothesized deeper processing:
 Questions about attractiveness and occupation


Kirkland, Reynolds and Pezdek (1992)
METHODS

Subjects

30 subjects
 24 in experimental group
 6 in control group
 All Mac undergrads
 Age range 18-24, Mean 20
METHODS

Stimulus/Materials

Study Task



32 faces
Experimental group
 Each Face paired with one question
Control group
 No questions presented
METHODS

Stimulus/Materials

Recognition Task



60 faces (28 novel)
Have you seen this face in the previous presentation?
 Yes/No responses
All subjects given same task
METHODS

Cover Story

Study Task – Subjects were told:
There will be questions about the faces
 They need to answer as quickly as possible the questions
 We are looking at how much you can tell about a person by
their appearance


Recognition Task:

Subjects were naïve of recognition task to follow the study
task
LEVELS OF PROCESSING

Questions:
1)
 2)
 3)
 4)

What is this person’s most attractive feature?
What job do you think this person has?
How old is this person?
What is this person’s gender?
Examine whether any of these questions will
result in deeper level of processing, measured
by accuracy of facial recognition
SLIDESHOW EXAMPLE: STUDY TASK
ATTRACTIVENESS?
AGE?
GENDER?
JOB?
SLIDESHOW EXAMPLE: RECOGNITION
TASK
DATA COLLECTION

Study Task


Recorded subject’s responses to questions
Recognition Task

Recorded if the subject answered yes or no
STUDY TASK DATA SHEET
Subject #
Question Orders
Group Number
Picture #
S’s response
1
2
3
4
1
a
d
b
c
2
b
c
a
d
3
c
b
d
a
4
d
a
c
b
5
a
d
b
c
6
b
c
a
d
RECOGNITION TASK DATA SHEET
Subject #
Recognition Task Ss Response Sheet
Picture Number
1
2
3
4 S’s response
Recognition
task slide #'s
S’s Correct Responses
2
54
0
0
0
0
4
21
a
d
b
c
6
27
c
b
d
a
8
45
0
0
0
0
10
43
0
0
0
0
12
14
b
c
a
d
14
41
0
0
0
0
16
28
d
a
c
b
18
24
d
a
c
b
RESULTS

Group Results (Experimental & Control)

Independent t-test

Descriptives

One-way ANOVA

Post-hoc (Bonferroni)
GROUP STATISTICS
Group Statistics
Group
Sstotal
1
2
N
Mean
Std. Deviation
Std. Error Mean
24
49.4167
5.19964
1.06137
6
40.6667
6.37704
2.60342
INDEPENDENT T-TEST
Independent Samples Test
Levene's
Test for
Equality of
Variances
t-test for Equality of Means
95% Confidence
Interval of the
Difference
Ss
total
Equal
variances
assumed
Equal
variances
not
assumed
df
Sig.
(2-tailed)
Mean
Difference
Std. Error
Difference
F
Sig.
t
Lower
Upper
.033
.858
3.531
28
.001
8.75000
2.47783
3.67440
13.82560
3.112
6.760
.018
8.75000
2.81146
2.05373
15.44627
DESCRIPTIVES
Descriptives
Data
95% Confidence Interval for
Mean
N
1
2
3
4
Total
Mean
Std. Deviation
Std. Error
Lower Bound
Upper Bound
Minimum
Maximum
24
6.7917
1.02062
.20833
6.3607
7.2226
5.00
8.00
24
6.0833
1.44212
.29437
5.4744
6.6923
3.00
8.00
24
5.2500
1.89393
.38660
4.4503
6.0497
1.00
8.00
24
5.7500
1.32698
.27087
5.1897
6.3103
3.00
8.00
96
5.9688
1.53865
.15704
5.6570
6.2805
1.00
8.00
ONE WAY ANOVA
ANOVA
Data
Sum of
Squares
Between
Groups
Mean
Square
df
30.115
3
10.038
194.792
92
2.117
224.906
95
Within Groups
Total
F
4.741
Sig.
.004
POST HOC
Multiple Comparisons
Data
Bonferroni
95% Confidence Interval
(I)
Questions
(J)
Questions
1
2
3
4
Mean Difference
(I-J)
Std. Error
2
.70833
.42005
.571
-.4243
1.8410
3
1.54167*
.42005
.002
.4090
2.6743
4
1.04167
.42005
.090
-.0910
2.1743
1
-.70833
.42005
.571
-1.8410
.4243
3
.83333
.42005
.301
-.2993
1.9660
4
.33333
.42005
1.000
-.7993
1.4660
1
-1.54167*
.42005
.002
-2.6743
-.4090
2
-.83333
.42005
.301
-1.9660
.2993
4
-.50000
.42005
1.000
-1.6327
.6327
1
-1.04167
.42005
.090
-2.1743
.0910
2
-.33333
.42005
1.000
-1.4660
.7993
3
.50000
.42005
1.000
-.6327
1.6327
*. The mean difference is significant at the 0.05 level.
Sig.
Lower Bound
Upper Bound
LIMITATIONS OF CURRENT STUDY

1) Response time:
5 second time limit
 Subjects provided arbitrary responses
 May have focused more on the question than actual
face
 Further studies: allow slightly more time for subjects’
responses

LIMITATIONS OF CURRENT STUDY

2) Occupation Question:
Was predicted to elicit deeper processing
 Answer didn’t require face processing
 Future studies: questions relying more on facial
features
 (I.e ethnicity, cosmetic surgery)

LIMITATIONS OF CURRENT STUDY

3) Facial Images:





Atypical facial images compared to participants and
people within the participants’ environment
Non significant results maybe due to quality of faces
Faces presented in grey-scale : require deeper
processing
Future studies: Use of coloured images is more realistic
Use more updated faces similar to those within
participants’ social environment
LIMITATIONS OF CURRENT STUDY

4) Number of Images:
Study task: 32 faces
 Recognition task: 60 faces
 Future studies: More faces in study and recognition
tasks
 Increase power

LIMITATIONS OF CURRENT STUDY

5) Control Group:
Smaller than experimental group
 Future studies:
 Larger number of subjects in control group size =
increase power
 Within-subjects control group:
 Have some pictures without any questions in the
slideshow

IMPLICATIONS

If significant:
Faces and words are processed similarly
 Improve peoples ability to remember new
acquaintances
 Eyewitness testimony

CONNECTIONS TO PREVIOUS
RESEARCH



Verbalization and conceptualization of faces lead to
better facial recognition
 Itoh, 2005; Bruce & Valentine, 1985
Improved memory when face is paired with question,
and when the answers are generated
 Geghman & Multhaup, 2004
Levels of processing may have had an effect on facial
recognition
 Craik, & Tulving, 1975
CONNECTIONS TO PREVIOUS
RESEARCH

Word memory vs. Facial memory

Mechanisms by which words are processed may not
be the same mechanisms employed in facial
recognition

Similar processing may be involved
FUTURE RESEARCH

Intentional vs. Incidental

Previous works show there is no difference in
memory if the learning is incidental or intentional


Craik, & Tulving, 1975
Examine if intentional or incidental learning has an
effect on facial recognition
FUTURE RESEARCH


Facial images

Examine the recognition of faces more typically seen
in the subject’s environment

Investigating recognition of faces of varying
ethnicities
Neuroimaging: fMRI
Examine areas of activation between different
questions
 Compare word processing to facial processing
